Computational models of angiogenesis: VEGF and its receptors in vitro and in vivo.

摘要

Angiogenesis, or neovascularization, is the growth of new blood vessels from preexisting microvasculature. It plays a crucial role in development and in normal adult vascular responses (such as wound healing, exercising muscle, ovulation and pregnancy). It is also involved in a broad range of diseases, including the top three causes of mortality in the western world: cardiovascular disease, cancer and stroke. In ischemic diseases (e.g. heart disease, stroke, peripheral artery disease) induction of angiogenesis would increase perfusion and protect tissue. In diseases of ectopic or hyper-vascularization (e.g. cancers, age-related macular degeneration and arthritis), inhibition of angiogenesis is a promising therapeutic strategy.; Members of the vascular endothelial growth factor (VEGF) cytokine family are critical regulators of angiogenesis. These secreted proteins bind to several receptor tyrosine kinases (VEGFRs) on endothelial cells, activating the receptors and initiating angiogenesis-related intracellular signal transduction. VEGF is actively being investigated both as a pro-angiogenic molecule, and as a target for the inhibition of neovascular growth. The multiplicity of VEGF proteins and VEGF receptors and co-receptors, along with the complexity of their interaction network, drove the development of mathematical models that could be used to understand the behavior of the VEGF system.; In this series of studies, we construct a set of computational models spanning multiple levels of biological organization to simulate in vitro experiments and in vivo tissue physiology and pathology. We use experimental data to provide parameters for the simulations, and validate the models using independent experiments. The results of these simulations will predict the behavior of the VEGF-VEGF Receptor system in various in vitro and in vivo situations, and will be applied to both skeletal muscle of the rat and human (both healthy and diseased), as well as to human breast cancer. We test, in silico , targeted therapies for both pro-angiogenesis in peripheral arterial disease (e.g. VEGF gene delivery, cell therapy chronic exercise training) and anti-angiogenesis (e.g. VEGF receptor knockdown, antibodies blocking VEGF signaling) in breast cancer. The mathematical models demonstrate an ability to predict not only which therapies are most effective, but which subpopulations of patients may benefit from particular therapies.